class_docstr: class object to do uniform sampling
class_docstr_tok: ["class","object","to","do","uniform","sampling"]
code: def extracted_reverse_subgraphs_per_type(self):
      sg_d = {}
      sg_src_range_d = {}
      for etype, edge_list in self.edge_list_dict.items():
          (
              sg_d[etype],
              sg_src_range_d[etype],
          ) = get_subgraph_and_src_range_from_edgelist(
              edge_list, is_mg=not (self.single_gpu), reverse_edges=True
          )
      return sg_d, sg_src_range_d
  
file_path: cugraph/python/cugraph/cugraph/gnn/dgl_extensions/dgl_uniform_sampler.py
imports: from functools import cached_property
  import cugraph
  import cudf
  import cupy
  from cugraph.gnn.dgl_extensions.utils.sampling import sample_cugraph_graphs, get_subgraph_and_src_range_from_edgelist, get_underlying_dtype_from_sg
  from cugraph.gnn.dgl_extensions.utils.sampling import src_n, dst_n
label_desc: Use image node_id 8 for calling the DGLUniformSampler obj's underlying member method code with example usage: obj.extracted_reverse_subgraphs_per_type() and returns: sg_d,  sg_src_range_d